{"title":"运动学未知的速度控制移动机械臂的预定义时间同步全身控制","authors":"Peng Yu;Siming Ma;Ning Tan","doi":"10.1109/TIE.2025.3553164","DOIUrl":null,"url":null,"abstract":"The integration of wheeled mobile platforms and robotic manipulators presents challenges in deriving an accurate kinematic model of wheeled mobile manipulators (WMMs). This article investigates the whole-body kinematic control problem for velocity-controlled WMMs with unknown kinematics. We prove that conventional zeroing dynamics (ZD) models are not predefined-time-synchronized (PTS) stable and propose a predefined-time-synchronized ZD (PTS-ZD) model. This PTS-ZD model is subsequently utilized to address the whole-body inverse kinematics problem of WMMs. In addition, an iterative gradient dynamics (IGD) method is proposed to learn the unknown combined Jacobian matrix of WMMs. By integrating the PTS-ZD model with the IGD-based method, we propose a model-free algorithm to address the kinematic trajectory tracking challenge in WMMs with unknown kinematics. The proposed algorithm ensures that the tracking errors across different dimensions converge to zero synchronously within a predefined time. The model-free nature of the algorithm enables efficient and rapid adaptation to various WMM configurations. Finally, the effectiveness of the proposed method is validated through simulations and experiments on different WMMs.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 10","pages":"10423-10433"},"PeriodicalIF":7.2000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predefined-Time-Synchronized Whole-Body Control of Velocity-Controlled Mobile Manipulators With Unknown Kinematics\",\"authors\":\"Peng Yu;Siming Ma;Ning Tan\",\"doi\":\"10.1109/TIE.2025.3553164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integration of wheeled mobile platforms and robotic manipulators presents challenges in deriving an accurate kinematic model of wheeled mobile manipulators (WMMs). This article investigates the whole-body kinematic control problem for velocity-controlled WMMs with unknown kinematics. We prove that conventional zeroing dynamics (ZD) models are not predefined-time-synchronized (PTS) stable and propose a predefined-time-synchronized ZD (PTS-ZD) model. This PTS-ZD model is subsequently utilized to address the whole-body inverse kinematics problem of WMMs. In addition, an iterative gradient dynamics (IGD) method is proposed to learn the unknown combined Jacobian matrix of WMMs. By integrating the PTS-ZD model with the IGD-based method, we propose a model-free algorithm to address the kinematic trajectory tracking challenge in WMMs with unknown kinematics. The proposed algorithm ensures that the tracking errors across different dimensions converge to zero synchronously within a predefined time. The model-free nature of the algorithm enables efficient and rapid adaptation to various WMM configurations. Finally, the effectiveness of the proposed method is validated through simulations and experiments on different WMMs.\",\"PeriodicalId\":13402,\"journal\":{\"name\":\"IEEE Transactions on Industrial Electronics\",\"volume\":\"72 10\",\"pages\":\"10423-10433\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2025-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Industrial Electronics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10947570/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10947570/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Predefined-Time-Synchronized Whole-Body Control of Velocity-Controlled Mobile Manipulators With Unknown Kinematics
The integration of wheeled mobile platforms and robotic manipulators presents challenges in deriving an accurate kinematic model of wheeled mobile manipulators (WMMs). This article investigates the whole-body kinematic control problem for velocity-controlled WMMs with unknown kinematics. We prove that conventional zeroing dynamics (ZD) models are not predefined-time-synchronized (PTS) stable and propose a predefined-time-synchronized ZD (PTS-ZD) model. This PTS-ZD model is subsequently utilized to address the whole-body inverse kinematics problem of WMMs. In addition, an iterative gradient dynamics (IGD) method is proposed to learn the unknown combined Jacobian matrix of WMMs. By integrating the PTS-ZD model with the IGD-based method, we propose a model-free algorithm to address the kinematic trajectory tracking challenge in WMMs with unknown kinematics. The proposed algorithm ensures that the tracking errors across different dimensions converge to zero synchronously within a predefined time. The model-free nature of the algorithm enables efficient and rapid adaptation to various WMM configurations. Finally, the effectiveness of the proposed method is validated through simulations and experiments on different WMMs.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.